Handbook of Research on Big Data Clustering and Machine Learning

Handbook of Research on Big Data Clustering and Machine Learning

Indexed In: SCOPUS
Release Date: October, 2019|Copyright: © 2020 |Pages: 478
DOI: 10.4018/978-1-7998-0106-1
ISBN13: 9781799801061|ISBN10: 1799801063|EISBN13: 9781799801078
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Description & Coverage
Description:

As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary.

The Handbook of Research on Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Behavioral Analytics
  • Business Information Systems
  • Business Mathematics
  • Cohort Analysis
  • Contextual Data Modeling
  • Marketing Analytics
  • Operations Research
  • Project Management
  • Supply Chain Management
  • Telecommunications
Table of Contents
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Editor/Author Biographies

Fausto Pedro Marquez works at UCLM as Full Professor (Accredited as Full Professor from 2013), Spain, Honorary Senior Research Fellow at Birmingham University, UK, Lecturer at the Postgraduate European Institute, and he has been Senior Manager in Accenture (2013-2014). He obtained his European PhD with a maximum distinction. He has been distingueed with the prices: Advancement Prize for Management Science and Engineering Management Nominated Prize (2018), First International Business Ideas Competition 2017 Award (2017); Runner (2015), Advancement (2013) and Silver (2012) by the International Society of Management Science and Engineering Management (ICMSEM); Best Paper Award in the international journal of Renewable Energy (Impact Factor 3.5) (2015). He has published more than 150 papers (65% ISI, 30% JCR and 92% internationals), some recognized as: “Renewable Energy” (as “Best Paper 2014”); “ICMSEM” (as “excellent”), “Int. J. of Automation and Computing” and “IMechE Part F: J. of Rail and Rapid Transit” (most downloaded), etc. He is author and editor of 25 books (Elsevier, Springer, Pearson, Mc-GrawHill, Intech, IGI, Marcombo, AlfaOmega,…), and 5 patents. He is Editor of 5 Int. Journals, Committee Member more than 40 Int. Conferences. He has been Principal Investigator in 4 European Projects, 5 National Projects, and more than 150 projects for Universities, Companies, etc. His main interest are: Maintenance Management, Renewable Energy, Transport, Advanced Analytics, Data Science. He is Director of www.ingeniumgroup.eu.

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